Pub Date : 2025-12-13DOI: 10.1016/j.mechatronics.2025.103449
Lissia L. Barbosa , Joseph P. Dutkowsky , Sunil K. Agrawal
Purpose
To evaluate the current evidence on Horse-Riding Simulators (HRS) as therapeutic alternatives to traditional hippotherapy and identify gaps in design and application.
Materials and Methods
A systematic review was conducted on studies involving HRS interventions. A total of 1754 English-language articles were screened, with 45 meeting the inclusion criteria for analysis.
Results
Forty-five studies were analyzed, mostly using commercial simulators and some custom-built devices. Intervention durations ranged from single sessions to 20 weeks across various populations. Randomized controlled trials represented 53.3 %, but overall evidence quality was low, with 37.8 % rated high risk of bias. Despite this, 93.3 % reported positive effects on balance, posture, and motor function, though comparisons with traditional hippotherapy remain inconclusive.
Conclusions
HRS present a promising therapeutic option where access to hippotherapy is limited, but current designs remain limited in their ability to fully simulate equine movement and sensory input. Future developments should focus on incorporating realistic and variable seat motion, multisensory feedback, and immersive virtual environments to maximize therapeutic outcomes.
{"title":"Hippotherapy simulators in physical rehabilitation: A systematic review","authors":"Lissia L. Barbosa , Joseph P. Dutkowsky , Sunil K. Agrawal","doi":"10.1016/j.mechatronics.2025.103449","DOIUrl":"10.1016/j.mechatronics.2025.103449","url":null,"abstract":"<div><h3>Purpose</h3><div>To evaluate the current evidence on Horse-Riding Simulators (HRS) as therapeutic alternatives to traditional hippotherapy and identify gaps in design and application.</div></div><div><h3>Materials and Methods</h3><div>A systematic review was conducted on studies involving HRS interventions. A total of 1754 English-language articles were screened, with 45 meeting the inclusion criteria for analysis.</div></div><div><h3>Results</h3><div>Forty-five studies were analyzed, mostly using commercial simulators and some custom-built devices. Intervention durations ranged from single sessions to 20 weeks across various populations. Randomized controlled trials represented 53.3 %, but overall evidence quality was low, with 37.8 % rated high risk of bias. Despite this, 93.3 % reported positive effects on balance, posture, and motor function, though comparisons with traditional hippotherapy remain inconclusive.</div></div><div><h3>Conclusions</h3><div>HRS present a promising therapeutic option where access to hippotherapy is limited, but current designs remain limited in their ability to fully simulate equine movement and sensory input. Future developments should focus on incorporating realistic and variable seat motion, multisensory feedback, and immersive virtual environments to maximize therapeutic outcomes.</div></div>","PeriodicalId":49842,"journal":{"name":"Mechatronics","volume":"114 ","pages":"Article 103449"},"PeriodicalIF":3.1,"publicationDate":"2025-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145737133","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-12DOI: 10.1016/j.mechatronics.2025.103448
Jan Inge Dyrhaug, Henrik M. Schmidt-Didlaukies, Kristin Y. Pettersen, Jan Tommy Gravdahl
This paper proposes a robust impedance control method for redundant robots that achieves compliant interaction with unknown environments while rejecting model errors and disturbances. The approach combines a nominal impedance controller with a generalized super-twisting algorithm (GSTA), using a sliding variable that robustly enforces the desired impedance relationship. A geometric formulation based on quaternion kinematics ensures that the stiffness and damping are physically meaningful and geometrically consistent in both position and orientation. Global asymptotic and finite-time stability are proven under bounded disturbances, and the method is experimentally validated on a 7-degree of freedom (DOF) Franka Panda robot. Compared to conventional sliding mode controllers, the proposed method significantly reduces chattering while maintaining robust tracking performance.
{"title":"Super-twisting impedance control of redundant robots","authors":"Jan Inge Dyrhaug, Henrik M. Schmidt-Didlaukies, Kristin Y. Pettersen, Jan Tommy Gravdahl","doi":"10.1016/j.mechatronics.2025.103448","DOIUrl":"10.1016/j.mechatronics.2025.103448","url":null,"abstract":"<div><div>This paper proposes a robust impedance control method for redundant robots that achieves compliant interaction with unknown environments while rejecting model errors and disturbances. The approach combines a nominal impedance controller with a generalized super-twisting algorithm (GSTA), using a sliding variable that robustly enforces the desired impedance relationship. A geometric formulation based on quaternion kinematics ensures that the stiffness and damping are physically meaningful and geometrically consistent in both position and orientation. Global asymptotic and finite-time stability are proven under bounded disturbances, and the method is experimentally validated on a 7-degree of freedom (DOF) Franka Panda robot. Compared to conventional sliding mode controllers, the proposed method significantly reduces chattering while maintaining robust tracking performance.</div></div>","PeriodicalId":49842,"journal":{"name":"Mechatronics","volume":"114 ","pages":"Article 103448"},"PeriodicalIF":3.1,"publicationDate":"2025-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145737132","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-12DOI: 10.1016/j.mechatronics.2025.103450
Ye Li, Aiguo Song, Jianwei Lai, Ye Lu, Huijun Li
Robot-assisted training has demonstrated significant potential in facilitating motor function recovery for stroke patients with hemiplegia. Among various rehabilitation strategies, the assist-as-needed (AAN) strategy, which promotes user participation while minimizing robotic intervention based on task performance or physiological states, has been widely adopted in rehabilitation robotics. This paper presents a novel variable admittance velocity field AAN controller integrated with spasticity detection capability. The primary objective was to develop a control strategy that enables upper limb trajectory tracking while ensuring training safety. First, we designed an admittance-controlled velocity field controller that achieves the AAN property through adaptive adjustment of admittance parameters. The velocity field design ensures precise trajectory tracking while maintaining temporal flexibility. Second, we propose an sEMG-based spasticity detection method that utilizes a Long Short-Term Memory (LSTM) network to model elbow spasticity patterns. In addition, a smooth velocity-switching function is designed to implement slow stretching of the affected limb during the spasticity phase. The performance of the controller was experimentally validated on both healthy subjects and post-stroke patients using a planar upper-limb rehabilitation robotic system. The results demonstrated that the proposed controller achieved better trajectory tracking accuracy and enhanced AAN performance compared to traditional force-field controller and impedance-based controller, and was capable of adjusting velocity upon the detection of subject spasticity.
{"title":"Velocity field assist-as-needed controller for upper limb rehabilitation with sEMG-based spasticity detection","authors":"Ye Li, Aiguo Song, Jianwei Lai, Ye Lu, Huijun Li","doi":"10.1016/j.mechatronics.2025.103450","DOIUrl":"10.1016/j.mechatronics.2025.103450","url":null,"abstract":"<div><div>Robot-assisted training has demonstrated significant potential in facilitating motor function recovery for stroke patients with hemiplegia. Among various rehabilitation strategies, the assist-as-needed (AAN) strategy, which promotes user participation while minimizing robotic intervention based on task performance or physiological states, has been widely adopted in rehabilitation robotics. This paper presents a novel variable admittance velocity field AAN controller integrated with spasticity detection capability. The primary objective was to develop a control strategy that enables upper limb trajectory tracking while ensuring training safety. First, we designed an admittance-controlled velocity field controller that achieves the AAN property through adaptive adjustment of admittance parameters. The velocity field design ensures precise trajectory tracking while maintaining temporal flexibility. Second, we propose an sEMG-based spasticity detection method that utilizes a Long Short-Term Memory (LSTM) network to model elbow spasticity patterns. In addition, a smooth velocity-switching function is designed to implement slow stretching of the affected limb during the spasticity phase. The performance of the controller was experimentally validated on both healthy subjects and post-stroke patients using a planar upper-limb rehabilitation robotic system. The results demonstrated that the proposed controller achieved better trajectory tracking accuracy and enhanced AAN performance compared to traditional force-field controller and impedance-based controller, and was capable of adjusting velocity upon the detection of subject spasticity.</div></div>","PeriodicalId":49842,"journal":{"name":"Mechatronics","volume":"114 ","pages":"Article 103450"},"PeriodicalIF":3.1,"publicationDate":"2025-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145737235","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-10DOI: 10.1016/j.mechatronics.2025.103447
Ryutaro Tokuyama, Takenori Atsumi
Hard disk drives (HDDs) are essential for large-scale data management in modern AI-oriented server infrastructures. This paper proposes a novel control strategy to improve the precision of magnetic-head positioning. The core of our methodology is a frequency-domain framework, the Robust Controller Bode (RCBode) plot, which provides an intuitive platform for loop-shaping filter design based on classical control theory. We further generalize this method to address Dual-Input Single-Output (DISO) configurations, specifically for the dual-stage actuator architectures in HDDs. The performance of the proposed control scheme was validated through benchmark scenarios, demonstrating a strong correlation with empirical data and confirming its effectiveness and practical utility.
{"title":"RCBode plot-based controller design for dual-stage actuators in HDDs","authors":"Ryutaro Tokuyama, Takenori Atsumi","doi":"10.1016/j.mechatronics.2025.103447","DOIUrl":"10.1016/j.mechatronics.2025.103447","url":null,"abstract":"<div><div>Hard disk drives (HDDs) are essential for large-scale data management in modern AI-oriented server infrastructures. This paper proposes a novel control strategy to improve the precision of magnetic-head positioning. The core of our methodology is a frequency-domain framework, the Robust Controller Bode (RCBode) plot, which provides an intuitive platform for loop-shaping filter design based on classical control theory. We further generalize this method to address Dual-Input Single-Output (DISO) configurations, specifically for the dual-stage actuator architectures in HDDs. The performance of the proposed control scheme was validated through benchmark scenarios, demonstrating a strong correlation with empirical data and confirming its effectiveness and practical utility.</div></div>","PeriodicalId":49842,"journal":{"name":"Mechatronics","volume":"114 ","pages":"Article 103447"},"PeriodicalIF":3.1,"publicationDate":"2025-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145737236","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-02DOI: 10.1016/j.mechatronics.2025.103438
Bo You , Haiyu She , Jiayu Li , Chen Chen
This study proposes an integrated path-planning framework for fault-tolerant hexapod robots navigating unstructured environments, addressing challenges posed by leg joint failures. The framework combines an enhanced A* algorithm with an adaptive Dynamic Window Approach (DWA) to improve navigation robustness. The A* algorithm incorporates a hazard-based model assessing terrain features like slopes, obstacles, and trenches, optimizing global paths by refining heuristic functions and minimizing path complexity to ensure safety and efficiency. The adaptive DWA dynamically adjusts local trajectories, balancing goal alignment, obstacle avoidance, stability, and energy efficiency through fault-specific evaluations, with weights tuned for optimal performance. Simulations and physical experiments demonstrate that the approach outperforms conventional methods, producing smoother, safer paths and enhancing stability across diverse terrains, even under fault conditions. This framework provides innovative solutions for reliable navigation in complex environments, offering significant potential for applications in search and rescue operations and extraterrestrial exploration, where adaptability and fault tolerance are critical for mission success.
{"title":"Hazard-constrained global-local path planning for fault-tolerant hexapod robots on unstructured terrain","authors":"Bo You , Haiyu She , Jiayu Li , Chen Chen","doi":"10.1016/j.mechatronics.2025.103438","DOIUrl":"10.1016/j.mechatronics.2025.103438","url":null,"abstract":"<div><div>This study proposes an integrated path-planning framework for fault-tolerant hexapod robots navigating unstructured environments, addressing challenges posed by leg joint failures. The framework combines an enhanced A* algorithm with an adaptive Dynamic Window Approach (DWA) to improve navigation robustness. The A* algorithm incorporates a hazard-based model assessing terrain features like slopes, obstacles, and trenches, optimizing global paths by refining heuristic functions and minimizing path complexity to ensure safety and efficiency. The adaptive DWA dynamically adjusts local trajectories, balancing goal alignment, obstacle avoidance, stability, and energy efficiency through fault-specific evaluations, with weights tuned for optimal performance. Simulations and physical experiments demonstrate that the approach outperforms conventional methods, producing smoother, safer paths and enhancing stability across diverse terrains, even under fault conditions. This framework provides innovative solutions for reliable navigation in complex environments, offering significant potential for applications in search and rescue operations and extraterrestrial exploration, where adaptability and fault tolerance are critical for mission success.</div></div>","PeriodicalId":49842,"journal":{"name":"Mechatronics","volume":"114 ","pages":"Article 103438"},"PeriodicalIF":3.1,"publicationDate":"2025-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145685366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-27DOI: 10.1016/j.mechatronics.2025.103437
Linkang Wang , Bai Chen , Tianzuo Chang , Jiafeng Yao , Hongtao Wu , Shuo Ding
Piezoelectric-driven XY compliant micro-positioning stages (XY-CMPSs) are widely employed in nanopositioning applications. However, existing designs face significant challenges in simultaneously achieving low geometric nonlinearity and a large workspace. This paper presents a novel XY-CMPS designed to overcome these limitations through a planar arrangement of multi-stage parallelogram mechanisms. To analyze the performance characteristics of the proposed stage, an amplification ratio model that accounts for both driving load and external equivalent load was established using the chain-based compliance matrix method (CCMM). On this basis, kinetostatic and dynamic analysis models were developed. The design parameters were optimized via a multi-objective optimization approach. Finite element analysis (FEA) results indicate that the proposed design reduces geometric nonlinearity by 62.35 % while achieving a larger workspace. Experimental evaluations on an XY-CMPS prototype demonstrated a workspace of 214.84 × 218.65 μm². The measured force-displacement relationship remains linear with a relative error below 3.17 %, confirming low geometric nonlinearity. The parasitic displacement was measured to be <2.5 μm (1.20 %). Furthermore, a motion tracking accuracy of up to 98.92 % was attained, which is attributed to the high natural frequency of approximately 210 Hz.
{"title":"Design and control of a novel XY compliant micro-positioning stage with low geometric nonlinearity and large workspace","authors":"Linkang Wang , Bai Chen , Tianzuo Chang , Jiafeng Yao , Hongtao Wu , Shuo Ding","doi":"10.1016/j.mechatronics.2025.103437","DOIUrl":"10.1016/j.mechatronics.2025.103437","url":null,"abstract":"<div><div>Piezoelectric-driven XY compliant micro-positioning stages (XY-CMPSs) are widely employed in nanopositioning applications. However, existing designs face significant challenges in simultaneously achieving low geometric nonlinearity and a large workspace. This paper presents a novel XY-CMPS designed to overcome these limitations through a planar arrangement of multi-stage parallelogram mechanisms. To analyze the performance characteristics of the proposed stage, an amplification ratio model that accounts for both driving load and external equivalent load was established using the chain-based compliance matrix method (CCMM). On this basis, kinetostatic and dynamic analysis models were developed. The design parameters were optimized via a multi-objective optimization approach. Finite element analysis (FEA) results indicate that the proposed design reduces geometric nonlinearity by 62.35 % while achieving a larger workspace. Experimental evaluations on an XY-CMPS prototype demonstrated a workspace of 214.84 × 218.65 μm². The measured force-displacement relationship remains linear with a relative error below 3.17 %, confirming low geometric nonlinearity. The parasitic displacement was measured to be <2.5 μm (1.20 %). Furthermore, a motion tracking accuracy of up to 98.92 % was attained, which is attributed to the high natural frequency of approximately 210 Hz.</div></div>","PeriodicalId":49842,"journal":{"name":"Mechatronics","volume":"114 ","pages":"Article 103437"},"PeriodicalIF":3.1,"publicationDate":"2025-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145600396","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-22DOI: 10.1016/j.mechatronics.2025.103427
Jian Xiong , Longwei Fan , Dayong Yang , Pengwen Xiong , Jie Lu , Weisheng Zhong
Visual SLAM algorithms suffer from errors in dynamic scenes due to interference from dynamic objects, leading to significant degradation in system accuracy. Existing deep learning-based methods for removing feature points of dynamic objects focus solely on actively moving objects with prior information, neglecting the dynamic characteristics of passive objects. To address this issue, we propose the concept of dynamic attribute recognition based on active–passive relationships; starting from the correlation between objects, we determine the dynamic attributes of passive objects based on the dynamic attributes of active objects. Building upon this, we propose a visual SLAM algorithm based on dynamic attribute recognition. First, YOLO is employed for object detection to identify the semantic information of objects and obtain their positional information. Then, the Euclidean distance is used to determine the affiliation between active and passive objects. Specifically, if the active object is a person, the Euclidean distance between the passive object and the hand keypoints determines their affiliation. Simultaneously, the Lucas-Kanade optical flow method and RANSAC are used to further assist in determining the dynamic attributes of both active and passive objects. Finally, feature points within the regions occupied by active and passive objects identified as dynamic are either removed or their weights are reduced, relying on static feature points to achieve camera pose estimation. Experimental results demonstrate that our algorithm reduces both the Absolute Trajectory Error (ATE) and Relative Pose Error (RPE) by over 90% compared to the original ORB-SLAM2 on high-dynamic sequences of the TUM dataset. Compared to similar algorithms such as DS-SLAM and Dyna-SLAM, our method exhibits superior accuracy and robustness in dynamic scenes containing both active and passive objects, with the tracking thread processing each frame in an average of only 29.36 ms. Our approach significantly enhances both the accuracy and real-time performance of SLAM algorithms in dynamic scenes.
{"title":"Visual SLAM algorithm based on dynamic attribute recognition in dynamic scenes","authors":"Jian Xiong , Longwei Fan , Dayong Yang , Pengwen Xiong , Jie Lu , Weisheng Zhong","doi":"10.1016/j.mechatronics.2025.103427","DOIUrl":"10.1016/j.mechatronics.2025.103427","url":null,"abstract":"<div><div>Visual SLAM algorithms suffer from errors in dynamic scenes due to interference from dynamic objects, leading to significant degradation in system accuracy. Existing deep learning-based methods for removing feature points of dynamic objects focus solely on actively moving objects with prior information, neglecting the dynamic characteristics of passive objects. To address this issue, we propose the concept of dynamic attribute recognition based on active–passive relationships; starting from the correlation between objects, we determine the dynamic attributes of passive objects based on the dynamic attributes of active objects. Building upon this, we propose a visual SLAM algorithm based on dynamic attribute recognition. First, YOLO is employed for object detection to identify the semantic information of objects and obtain their positional information. Then, the Euclidean distance is used to determine the affiliation between active and passive objects. Specifically, if the active object is a person, the Euclidean distance between the passive object and the hand keypoints determines their affiliation. Simultaneously, the Lucas-Kanade optical flow method and RANSAC are used to further assist in determining the dynamic attributes of both active and passive objects. Finally, feature points within the regions occupied by active and passive objects identified as dynamic are either removed or their weights are reduced, relying on static feature points to achieve camera pose estimation. Experimental results demonstrate that our algorithm reduces both the Absolute Trajectory Error (ATE) and Relative Pose Error (RPE) by over 90% compared to the original ORB-SLAM2 on high-dynamic sequences of the TUM dataset. Compared to similar algorithms such as DS-SLAM and Dyna-SLAM, our method exhibits superior accuracy and robustness in dynamic scenes containing both active and passive objects, with the tracking thread processing each frame in an average of only 29.36 ms. Our approach significantly enhances both the accuracy and real-time performance of SLAM algorithms in dynamic scenes.</div></div>","PeriodicalId":49842,"journal":{"name":"Mechatronics","volume":"113 ","pages":"Article 103427"},"PeriodicalIF":3.1,"publicationDate":"2025-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145579344","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-22DOI: 10.1016/j.mechatronics.2025.103428
A. Pawluchin , T.-L. Habich , T. Seel , I. Boblan
Pressure control forms the foundation for operating soft pneumatic actuators (SPAs). For effective motion or force control, however, the underlying pressure control must be both fast and accurate. This can be achieved either by placing the valve close to the actuator or by compensating for long pneumatic tubes through dynamic modeling. Tube compensation, however, is complex and difficult to implement, while direct valve mounting is often impractical because conventional proportional valves are large and heavy.
To overcome these limitations, a compact, custom-designed 3/3-valve unit (CVU) based on Festo’s VEAE piezoelectric valves is developed. The CVU supports pressures up to 6 bar, flow rates up to 70 l/min and control bandwidths exceeding 9 Hz. It is controlled using the presented data-driven approach, which eliminates the need for classical system identification and automatically adapts to different actuator volumes, resulting in high accuracy and simple deployment.
The control scheme employs a two-stage, data-driven architecture based on single-shot Gaussian process (GP) regression. First, the inverse static flow characteristics of each valve are modeled, compensating for valve-to-valve variability without manual mass-flow identification. Second, the CVU is adapted to the actuator’s state-dependent volume, improving accuracy and robustness to external disturbances. In both stages, only the pressure derivative is used, avoiding the need for additional flow sensors or external test benches and keeping the approach lightweight and low-cost. The CVU with the data-driven control method was validated on an antagonistic pneumatic arm with pneumatic artificial muscles (PAMs) and benchmarked against a manually tuned PID controller, a feedback-linearized controller based on analytical system inversion and a commercially available VEAB valve unit. Across all tests, the CVU with GP-based control achieved highly accurate pressure tracking and disturbance rejection. All hardware (CAD) and development code (m-code) are released as open source.
{"title":"Data-driven pressure controller using proportional piezoelectric valves for soft pneumatic actuators","authors":"A. Pawluchin , T.-L. Habich , T. Seel , I. Boblan","doi":"10.1016/j.mechatronics.2025.103428","DOIUrl":"10.1016/j.mechatronics.2025.103428","url":null,"abstract":"<div><div>Pressure control forms the foundation for operating soft pneumatic actuators (SPAs). For effective motion or force control, however, the underlying pressure control must be both fast and accurate. This can be achieved either by placing the valve close to the actuator or by compensating for long pneumatic tubes through dynamic modeling. Tube compensation, however, is complex and difficult to implement, while direct valve mounting is often impractical because conventional proportional valves are large and heavy.</div><div>To overcome these limitations, a compact, custom-designed 3/3-valve unit (CVU) based on Festo’s VEAE piezoelectric valves is developed. The CVU supports pressures up to 6<!--> <!-->bar, flow rates up to 70<!--> <!-->l/min and control bandwidths exceeding 9<!--> <!-->Hz. It is controlled using the presented data-driven approach, which eliminates the need for classical system identification and automatically adapts to different actuator volumes, resulting in high accuracy and simple deployment.</div><div>The control scheme employs a two-stage, data-driven architecture based on single-shot Gaussian process (GP) regression. First, the inverse static flow characteristics of each valve are modeled, compensating for valve-to-valve variability without manual mass-flow identification. Second, the CVU is adapted to the actuator’s state-dependent volume, improving accuracy and robustness to external disturbances. In both stages, only the pressure derivative is used, avoiding the need for additional flow sensors or external test benches and keeping the approach lightweight and low-cost. The CVU with the data-driven control method was validated on an antagonistic pneumatic arm with pneumatic artificial muscles (PAMs) and benchmarked against a manually tuned PID controller, a feedback-linearized controller based on analytical system inversion and a commercially available VEAB valve unit. Across all tests, the CVU with GP-based control achieved highly accurate pressure tracking and disturbance rejection. All hardware (CAD) and development code (m-code) are released as open source.</div></div>","PeriodicalId":49842,"journal":{"name":"Mechatronics","volume":"113 ","pages":"Article 103428"},"PeriodicalIF":3.1,"publicationDate":"2025-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145624184","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-21DOI: 10.1016/j.mechatronics.2025.103426
Ferhat Kaya , Caglar Conker
This manuscript addresses the problem of designing a robust input shaper capable of suppressing residual vibrations in flexible robotic and mechanical systems under modeling errors and parameter uncertainties, while also providing smooth reference commands.The proposed approach integrates Cycloid, Ramped Versine and Ramp (CPRVPR) functions with Zero Vibration (ZV, ZVD, and ZVDD) input shapers, optimizing their parameters using the Vibrating Particle System (VPS) Algorithm. Furthermore, the study proposes a novel multi-objective function that accounts for critical parameters of input shaping techniques in flexible robotic systems and the robustness constraints of Extra-Insensitive input shapers. The theoretical outcomes of the proposed command shaping approaches were experimentally validated through their application to a linear crane system. The effectiveness of the three proposed methods was demonstrated by comparing them against fifteen well-known input shaping techniques. The novel intelligent command shaping design was shown to effectively mitigate or eliminate residual vibrations in flexible systems, even under high levels of uncertainty.
{"title":"Design and multi-objective optimization of a novel robust command shaping technique for the tolerable level of residual vibration","authors":"Ferhat Kaya , Caglar Conker","doi":"10.1016/j.mechatronics.2025.103426","DOIUrl":"10.1016/j.mechatronics.2025.103426","url":null,"abstract":"<div><div>This manuscript addresses the problem of designing a robust input shaper capable of suppressing residual vibrations in flexible robotic and mechanical systems under modeling errors and parameter uncertainties, while also providing smooth reference commands<em>.</em>The proposed approach integrates Cycloid, Ramped Versine and Ramp (CPRVPR) functions with Zero Vibration (ZV, ZVD, and ZVDD) input shapers, optimizing their parameters using the Vibrating Particle System (VPS) Algorithm. Furthermore, the study proposes a novel multi-objective function that accounts for critical parameters of input shaping techniques in flexible robotic systems and the robustness constraints of Extra-Insensitive input shapers. The theoretical outcomes of the proposed command shaping approaches were experimentally validated through their application to a linear crane system. The effectiveness of the three proposed methods was demonstrated by comparing them against fifteen well-known input shaping techniques. The novel intelligent command shaping design was shown to effectively mitigate or eliminate residual vibrations in flexible systems, even under high levels of uncertainty.</div></div>","PeriodicalId":49842,"journal":{"name":"Mechatronics","volume":"113 ","pages":"Article 103426"},"PeriodicalIF":3.1,"publicationDate":"2025-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145579355","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The autonomous ground vehicles (AGVs) are expected to reliably track a planned path with high-accuracy in a wide variety of industry and civilian applications. Pure pursuit is widely used to solve this problem. However, most of the existing pure pursuit methods have the cutting-corner problem which results in poor path tracking performance when there are sharp turns. In this article, we learn from how the human drivers look ahead when they drive the vehicle to follow a road and propose the concept of path projected area for the first time which is similar to the driver perspective. An adaptive pure pursuit path tracking control method based on projected area is developed for AGVs, named PA-PP. First, a look-ahead distance is selected based on the predefined threshold of the path projected area in the method. Then, the velocity allocation method is introduced which also takes into account the path projected area. The optimal control command is generated through an adaptive controller. We verify the effectiveness of the PA-PP method in simulation and vehicle tests by comparing the performance of it with other three pure pursuit methods. The results show that the PA-PP method can not only improve the tracking robustness while the vehicle enters a turn, but also can result in a reduction of cumulative path tracking errors by nearly 31.09% in simulation test and 21.02% in vehicle experiment comparing to those of the classic pure pursuit algorithms.
{"title":"Driver perspective inspired pure pursuit path tracking control method for autonomous ground vehicles","authors":"Haojie Zhang , Rongmin Liang , Feng Jiang , Qing Li","doi":"10.1016/j.mechatronics.2025.103424","DOIUrl":"10.1016/j.mechatronics.2025.103424","url":null,"abstract":"<div><div>The autonomous ground vehicles (AGVs) are expected to reliably track a planned path with high-accuracy in a wide variety of industry and civilian applications. Pure pursuit is widely used to solve this problem. However, most of the existing pure pursuit methods have the cutting-corner problem which results in poor path tracking performance when there are sharp turns. In this article, we learn from how the human drivers look ahead when they drive the vehicle to follow a road and propose the concept of path projected area for the first time which is similar to the driver perspective. An adaptive pure pursuit path tracking control method based on projected area is developed for AGVs, named PA-PP. First, a look-ahead distance is selected based on the predefined threshold of the path projected area in the method. Then, the velocity allocation method is introduced which also takes into account the path projected area. The optimal control command is generated through an adaptive controller. We verify the effectiveness of the PA-PP method in simulation and vehicle tests by comparing the performance of it with other three pure pursuit methods. The results show that the PA-PP method can not only improve the tracking robustness while the vehicle enters a turn, but also can result in a reduction of cumulative path tracking errors by nearly 31.09% in simulation test and 21.02% in vehicle experiment comparing to those of the classic pure pursuit algorithms.</div></div>","PeriodicalId":49842,"journal":{"name":"Mechatronics","volume":"113 ","pages":"Article 103424"},"PeriodicalIF":3.1,"publicationDate":"2025-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145579365","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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